TokelyTHE COST OF BUILDING WITH AI
AI API pricing snapshot: October 2026
A reproducible snapshot of Tokely's enabled model rates, exact-model OpenRouter references and media billing units. Download the data and inspect the comparison method.
THE SHORT ANSWER
This snapshot covers 77 enabled Tokely models across text, image, video and audio, including 35 exact-model OpenRouter token references checked on 2026-10-09. It is published by Tokely and is not an independent market-wide ranking.
The catalog in this snapshot
What the matched text comparison shows
For the disclosed workload of 1M uncached input and 250K output tokens, Tokely has a lower estimate on 29 of 35 matched offers and a higher estimate on 6. The median signed price difference within this matched set is 59.6%. These are token-rate estimates before checkout/platform fees and taxes, not observed customer savings or performance results.
The matched set consists of models enabled in Tokely; it is not a random market sample. Changing the input/output mix can change both the difference and which offer costs less. Missing references are excluded from this statistic and stay visible as unmatched in the full table.
| Model | Tokely input / output | Tokely example | OpenRouter example | Difference vs OpenRouter |
|---|---|---|---|---|
| Gemini 3.1 Flash LiteGoogle | $0.050552 / $0.303312Cache read: $0.005056 | $0.12638 | $0.625$0.25 / $1.5 per 1M | 79.8% lower |
| Gemini 2.5 FlashGoogle | $0.060663 / $0.505924Cache read: $0.006067 | $0.187144 | $0.925$0.3 / $2.5 per 1M | 79.8% lower |
| Gemini 3.7 FlashGoogle | $0.151656 / $0.758279Cache read: $0.015166 | $0.341226 | $1.6875$0.75 / $3.75 per 1M | 79.8% lower |
| Gemini 3.8 FlashGoogle | $0.151656 / $0.758279Cache read: $0.015166 | $0.341226 | $1.6875$0.75 / $3.75 per 1M | 79.8% lower |
| GPT-5 CodexOpenAI | $0.126397 / $1.011175Cache read: $0.01264 | $0.379191 | Not matched | — |
| Gemini 3.5 Flash LiteGoogle | $0.218386 / $1.819882Cache read: $0.021839 | $0.673357 | $0.925$0.3 / $2.5 per 1M | 27.2% lower |
| GPT-6 LunaOpenAI | $0.404415 / $1.213245Cache read: $0.032354 | $0.707726 | $0.225$0.1 / $0.5 per 1M | 214.5% higher |
| Grok 4.3Grok | $0.505519 / $1.011038Cache read: $0.505519 | $0.758279 | $1.875$1.25 / $2.5 per 1M | 59.6% lower |
| Gemini 3.5 FlashGoogle | $0.303312 / $1.819868Cache read: $0.030332 | $0.758279 | $3.75$1.5 / $9 per 1M | 79.8% lower |
| DeepSeek V4.1 FlashDeepSeek | $0.4125 / $1.65Cache read: $0.00825 | $0.825 | $0.6$0.3 / $1.2 per 1M | 37.5% higher |
| GPT-6 SolOpenAI | $0.505588 / $1.516763Cache read: $0.040447 | $0.884779 | $4.5$2 / $10 per 1M | 80.3% lower |
| GPT-6.1 SolOpenAI | $0.505588 / $1.516763Cache read: $0.020224 | $0.884779 | $4.5$2 / $10 per 1M | 80.3% lower |
| GPT-5.6 TerraOpenAI | $0.505588 / $1.820115Cache read: $0.040447 | $0.960617 | $5$2 / $12 per 1M | 80.8% lower |
| Claude Sonnet 5Anthropic | $0.48532 / $2.4266Cache read: $0.048532 | $1.09197 | $4.5$2 / $10 per 1M | 75.7% lower |
| GPT-5.6 LunaOpenAI | $0.605 / $2.178Cache read: $0.0484 | $1.1495 | $0.5$0.2 / $1.2 per 1M | 129.9% higher |
| Gemini 2.5 ProGoogle | $0.505519 / $3.033113Cache read: $0.050552 | $1.263797 | $3.75$1.25 / $10 per 1M | 66.3% lower |
| Grok 4.5Grok | $0.80883 / $2.42649Cache read: $0.202208 | $1.415453 | $3.5$2 / $6 per 1M | 59.6% lower |
| Grok 4.6Grok | $0.80883 / $2.42649Cache read: $0.202208 | $1.415453 | $3.5$2 / $6 per 1M | 59.6% lower |
| Grok 4.7Grok | $0.80883 / $2.42649Cache read: $0.202208 | $1.415453 | $3.5$2 / $6 per 1M | 59.6% lower |
| Claude Sonnet 4.6Anthropic | $0.72798 / $3.6399Cache read: $0.072798 | $1.637955 | $6.75$3 / $15 per 1M | 75.7% lower |
| GPT-5.2 CodexOpenAI | $0.641667 / $5.133334Cache read: $0.064167 | $1.925001 | $5.25$1.75 / $14 per 1M | 63.3% lower |
| GPT-5.5OpenAI | $1.011175 / $4.550288Cache read: $0.101118 | $2.148747 | $12.5$5 / $30 per 1M | 82.8% lower |
| Claude Sonnet 5.5Anthropic | $0.970585 / $4.852925Cache read: $0.097059 | $2.183816 | $4.5$2 / $10 per 1M | 51.5% lower |
| Claude Opus 5.5Anthropic | $0.97064 / $4.8532Cache read: $0.048532 | $2.18394 | $9$4 / $20 per 1M | 75.7% lower |
| Gemini 3 ProGoogle | $0.833334 / $5.833334Cache read: $0.833334 | $2.291668 | Not matched | — |
| Gemini 3.1 ProGoogle | $0.833334 / $5.833334Cache read: $0.833334 | $2.291668 | Not matched | — |
| GPT-5.6 SolOpenAI | $1.263969 / $4.550288Cache read: $0.101118 | $2.401541 | $4.5$2 / $10 per 1M | 46.6% lower |
| GPT-5.1 CodexOpenAI | $1.008334 / $8.066667Cache read: $0.100834 | $3.025001 | $3.75$1.25 / $10 per 1M | 19.3% lower |
| GPT-5.3 CodexOpenAI | $1.05875 / $8.47Cache read: $0.105875 | $3.17625 | $5.25$1.75 / $14 per 1M | 39.5% lower |
| GPT-6 AstraOpenAI | $2.527938 / $7.583813Cache read: $0.202235 | $4.423891 | $22.5$10 / $50 per 1M | 80.3% lower |
| Claude Opus 4.6Anthropic | $2.426463 / $12.132313Cache read: $0.242647 | $5.459541 | $11.25$5 / $25 per 1M | 51.5% lower |
| Claude Opus 4.8Anthropic | $2.426463 / $12.132313Cache read: $0.242647 | $5.459541 | $11.25$5 / $25 per 1M | 51.5% lower |
| Claude Opus 5Anthropic | $2.426463 / $12.132313Cache read: $0.242647 | $5.459541 | $11.25$5 / $25 per 1M | 51.5% lower |
| Claude Opus 4.7Anthropic | $3.033079 / $12.132313Cache read: $0.242647 | $6.066157 | $11.25$5 / $25 per 1M | 46.1% lower |
| GPT-5.2OpenAI | $2.1175 / $16.94Cache read: $0.21175 | $6.3525 | $5.25$1.75 / $14 per 1M | 21.0% higher |
| GPT-5.4OpenAI | $3.025 / $13.6125Cache read: $0.3025 | $6.428125 | $6.25$2.5 / $15 per 1M | 2.8% higher |
| Kimi K3Moonshot | $4.125 / $20.625Cache read: $0.4125 | $9.28125 | $3.5$0.5 / $12 per 1M | 165.2% higher |
| Claude Fable 5Anthropic | $4.852925 / $24.264625Cache read: $0.485293 | $10.919081 | $22.5$10 / $50 per 1M | 51.5% lower |
What we cannot infer from one snapshot
There is no month-over-month or year-over-year price trend in this release. There are no measured latency, uptime or quality rankings. Media variants are listed with their own units and settings; the report does not turn different images or video lengths into equivalent products.
Data, dates and reproduction
Use the price index, the archived October JSON and the current text CSV. The methodology defines matching, formulas and exclusions. Cite this dated report alongside the dataset when discussing its findings.
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